Democratic Republic of the Congo Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 23 March 2026.
Here you’ll find a curated sample of 100 key cities from Democratic Republic of the Congo, each with essential data points such as latitude, longitude, administrative region, and other relevant attributes.
This preview is extracted from our full dataset, which includes a total of 36908 geographic locations across Democratic Republic of the Congo.
Whether you’re working on mapping, analytics, or app development, the data is available for both personal and commercial use.
All entries can be downloaded in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML.
Capital Highlight: The official capital city of Democratic Republic of the Congo is Kinshasa.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 922746 | Kyambele | Kiambele,Kyambele | CD | Lualaba | Mutshatsha | -11.31667 | 25.45 | 0 | Africa/Lubumbashi | populated place | |
| 213400 | Kiamba | CD | Nord Kivu | Lubero | -0.6 | 28.98333 | 0 | Africa/Lubumbashi | populated place | ||
| 8279624 | Yaongo | CD | Mongala | Bongandanga | 2.02366 | 22.03995 | 0 | Africa/Kinshasa | populated place | ||
| 217893 | Boyombe | CD | Tshuapa | Monkoto | -1.86667 | 20.96667 | 0 | Africa/Kinshasa | populated place | ||
| 208507 | Mugbodi | CD | Tshopo | Bafwasende | 0.66667 | 27.6 | 0 | Africa/Lubumbashi | populated place | ||
| 212978 | Kimadiobo | CD | Haut-Lomami | Kamina | -8.85 | 25.4 | 0 | Africa/Lubumbashi | populated place | ||
| 8445799 | Kikwe-Kavunga | CD | Kwango | Kenge | -4.4348 | 17.59186 | 0 | Africa/Kinshasa | populated place | ||
| 8198048 | Basende | CD | Bas-Uele | Bondo | 3.92163 | 24.77267 | 0 | Africa/Lubumbashi | populated place | ||
| 220334 | Amolia | CD | Bas-Uele | Bambesa | 3.01667 | 26.2 | 0 | Africa/Lubumbashi | populated place | ||
| 204092 | Yahisuli | Yahisuli,Yahisulu | CD | Tshopo | Isangi | -0.1073 | 24.02434 | 0 | Africa/Lubumbashi | populated place | |
| 205546 | Silingbi | CD | Bas-Uele | Ango | 3.87224 | 26.10712 | 0 | Africa/Lubumbashi | populated place | ||
| 215859 | Inkekete | CD | Kasai | Dekese | -2.61667 | 21.88333 | 0 | Africa/Lubumbashi | populated place | ||
| 8438857 | Denda | CD | Kasai-Central | Luiza | -7.32904 | 22.27986 | 0 | Africa/Lubumbashi | populated place | ||
| 8274455 | Kiala-Balakwilu | CD | Kwilu | Masi-Manimba | -5.07168 | 17.68275 | 0 | Africa/Kinshasa | populated place | ||
| 206748 | Okangakoie | CD | Sankuru | Lodja | -4.03333 | 23.15 | 0 | Africa/Lubumbashi | populated place | ||
| 218481 | Bokundola | CD | Mongala | Lisala | 2.5093 | 21.07629 | 0 | Africa/Kinshasa | populated place | ||
| 212040 | Lelema | CD | Tshopo | Isangi | -0.17974 | 24.00428 | 0 | Africa/Lubumbashi | populated place | ||
| 8284319 | Kalamba | CD | Kasai-Central | Kazumba | -6.33164 | 22.34078 | 0 | Africa/Lubumbashi | populated place | ||
| 10010962 | Kiyalo | CD | Tanganyika | Kalemie Ville | -6.31358 | 28.7767 | 0 | Africa/Lubumbashi | populated place | ||
| 8062274 | Mbule | CD | Bas-Uele | Poko | 2.99621 | 26.69783 | 0 | Africa/Lubumbashi | populated place | ||
| 208906 | Mokole | CD | Tshopo | Bafwasende | 0.03333 | 27.58333 | 0 | Africa/Lubumbashi | populated place | ||
| 387607 | Kasombo | CD | South Kivu | Fizi | -3.71306 | 29.12028 | 0 | Africa/Lubumbashi | populated place | ||
| 2314621 | Kimbangu | CD | Kwango | Kasongo-Lunda | -7.72184 | 17.35635 | 0 | Africa/Kinshasa | populated place | ||
| 8329511 | Miombe Mwavi Deuxième | CD | Lomami | Kabinda | -5.80363 | 24.61072 | 0 | Africa/Lubumbashi | populated place | ||
| 1099071 | Dikusu | CD | Haut-Katanga | Sakania | -12.17836 | 27.99129 | 0 | Africa/Lubumbashi | populated place | ||
| 215301 | Kafumbu | CD | Lomami | Ngandajika | -6.72297 | 23.7835 | 0 | Africa/Lubumbashi | populated place | ||
| 2314170 | Kisefu | CD | Kwilu | Masi-Manimba | -4.69462 | 17.62146 | 0 | Africa/Kinshasa | populated place | ||
| 8281481 | Mabuna | CD | Ituri | Mambasa | 0.72599 | 28.58097 | 0 | Africa/Lubumbashi | populated place | ||
| 11952146 | Nyamussasi Port | CD | Ituri | Irumu | 1.41229 | 30.46865 | 0 | Africa/Lubumbashi | populated place | ||
| 214936 | Kalia | CD | Nord Kivu | Lubero | -0.66667 | 29.23333 | 0 | Africa/Lubumbashi | populated place | ||
| 2315328 | Ivua | Ivua,Vwa | CD | Bas-Congo | Madimba | -5.57655 | 15.23502 | 0 | Africa/Kinshasa | populated place | |
| 10226398 | Kisonga | CD | Haut-Katanga | Kipushi Ville | -11.72329 | 27.28038 | 0 | Africa/Lubumbashi | populated place | ||
| 9946358 | Kantambo | CD | Haut-Lomami | Malemba-Nkulu | -7.96994 | 27.17771 | 0 | Africa/Lubumbashi | populated place | ||
| 2316234 | Bunda-Kifilu | CD | Kwango | Feshi | -6.01722 | 17.5868 | 0 | Africa/Kinshasa | populated place | ||
| 8252371 | Kai Tshianga | CD | Bas-Congo | Moanda | -5.85828 | 12.69859 | 0 | Africa/Kinshasa | populated place | ||
| 10041176 | Kibondo | CD | Haut-Lomami | Bukama | -8.90986 | 26.38064 | 0 | Africa/Lubumbashi | populated place | ||
| 208974 | Monzamboli | Modjamboli,Monzamboli | CD | Mongala | Bumba | 2.4737 | 22.10238 | 0 | Africa/Kinshasa | populated place | |
| 214421 | Kangara | Kangala,Kangara | CD | Mai-Ndombe | Oshwe | -3.64009 | 20.31629 | 0 | Africa/Kinshasa | populated place | |
| 8520794 | Nioka | CD | Lomami | Luilu | -7.25008 | 23.94052 | 0 | Africa/Lubumbashi | populated place | ||
| 206964 | Noimbo | CD | Bas-Uele | Buta | 3.10024 | 25.46629 | 0 | Africa/Lubumbashi | populated place | ||
| 203686 | Yangwa | CD | Tshopo | Basoko | 1.51667 | 23.58333 | 0 | Africa/Lubumbashi | populated place | ||
| 216124 | Hoshi | CD | Tanganyika | Kalemie Ville | -5.53333 | 29.28333 | 0 | Africa/Lubumbashi | populated place | ||
| 218032 | Botende | CD | Sankuru | Lomela | -1.9107 | 22.85485 | 0 | Africa/Lubumbashi | populated place | ||
| 8283725 | Tshimanga | CD | Kasai-Central | Kazumba | -6.20856 | 22.35096 | 0 | Africa/Lubumbashi | populated place | ||
| 210114 | Madjandala | CD | Bas-Uele | Poko | 2.2982 | 26.47588 | 0 | Africa/Lubumbashi | populated place | ||
| 212136 | Kwodjambi | CD | Haut-Uele | Watsa | 2.66667 | 29.13333 | 0 | Africa/Lubumbashi | populated place | ||
| 8447675 | Sha-Ndjamba-Lumbu | CD | Kwango | Kasongo-Lunda | -7.20062 | 18.48617 | 0 | Africa/Kinshasa | populated place | ||
| 2313461 | Lubisi | CD | Bas-Congo | Kimvula | -5.76517 | 16.08947 | 0 | Africa/Kinshasa | populated place | ||
| 2316839 | Bokonzi | Bokondji,Bokonzi,Bokundji,Makengo Bokonji,Makengo Bokonsi | CD | Sud-Ubangi | Kungu | 2.38072 | 18.69766 | 0 | Africa/Kinshasa | populated place | |
| 2314905 | Kiala-Longo | CD | Kwango | Kasongo-Lunda | -6.13387 | 16.93533 | 0 | Africa/Kinshasa | populated place | ||
| 204315 | Wamba-Moke | CD | Haut-Uele | Niangara | 3.27788 | 28.15541 | 0 | Africa/Lubumbashi | populated place | ||
| 8448077 | Mwamutunda | CD | Kwango | Kahemba | -7.10835 | 19.13832 | 0 | Africa/Kinshasa | populated place | ||
| 215912 | Imbambu | CD | Kasai | Dekese | -3.45 | 21.83333 | 0 | Africa/Lubumbashi | populated place | ||
| 219925 | Bafwazenge | CD | Tshopo | Bafwasende | 1.02452 | 26.84032 | 0 | Africa/Lubumbashi | populated place | ||
| 204977 | Tshidimba | CD | Kasai-Central | Dibaya | -6.67024 | 22.64792 | 0 | Africa/Lubumbashi | populated place | ||
| 922840 | Kilawale | Kiankwale,Kilawale,Kyankwale | CD | Lualaba | Lubudi | -10.33333 | 26.3 | 0 | Africa/Lubumbashi | populated place | |
| 2311771 | Pangi | CD | Mai-Ndombe | Kiri | -1.35 | 18.91667 | 0 | Africa/Kinshasa | populated place | ||
| 205009 | Tshindinda | Tshibinda,Tshidinda,Tshindinda | CD | Kasai | Luebo | -5.78856 | 21.34714 | 0 | Africa/Lubumbashi | populated place | |
| 8447684 | Makulula | CD | Kwango | Kahemba | -7.20242 | 18.83778 | 0 | Africa/Kinshasa | populated place | ||
| 220286 | Angodepala | CD | Haut-Uele | Dungu | 4.29494 | 28.53541 | 0 | Africa/Lubumbashi | populated place | ||
| 8325103 | Kafusie | CD | Bas-Congo | Mbanza-Ngungu | -5.31078 | 14.96986 | 0 | Africa/Kinshasa | populated place | ||
| 2314283 | Kintempe | CD | Bas-Congo | Luozi | -5.11072 | 13.60414 | 0 | Africa/Kinshasa | populated place | ||
| 10041052 | Kiungwe | CD | Haut-Lomami | Bukama | -8.16556 | 26.78714 | 0 | Africa/Lubumbashi | populated place | ||
| 8328112 | Gandu | CD | Bas-Congo | Mbanza-Ngungu | -5.17354 | 14.56268 | 0 | Africa/Kinshasa | populated place | ||
| 2314586 | Kimbili | CD | Kwilu | Masi-Manimba | -4.52412 | 17.9402 | 0 | Africa/Kinshasa | populated place | ||
| 10054809 | Tshangoma | CD | Lualaba | Lubudi | -9.97003 | 26.32066 | 0 | Africa/Lubumbashi | populated place | ||
| 220016 | Bafwadei | CD | Tshopo | Bafwasende | 1.66667 | 27.03333 | 0 | Africa/Lubumbashi | populated place | ||
| 2310848 | Yimbi-Fioti | CD | Kwango | Kenge | -4.83333 | 16.48333 | 0 | Africa/Kinshasa | populated place | ||
| 216495 | Gabo | CD | Lomami | Kabinda | -6.38826 | 24.65893 | 0 | Africa/Lubumbashi | populated place | ||
| 8462259 | Tshilanda | CD | Lualaba | Sandoa | -9.68717 | 23.67115 | 0 | Africa/Lubumbashi | populated place | ||
| 8448082 | Kahumbu | CD | Kwango | Kahemba | -7.09731 | 19.1332 | 0 | Africa/Kinshasa | populated place | ||
| 8275886 | Luteki | CD | Kwilu | Masi-Manimba | -5.15712 | 18.12308 | 0 | Africa/Kinshasa | populated place | ||
| 8024381 | Wodi | CD | Haut-Uele | Dungu | 3.85982 | 28.31404 | 0 | Africa/Lubumbashi | populated place | ||
| 8446359 | Kikwiti | CD | Kwilu | Masi-Manimba | -4.2176 | 18.0648 | 0 | Africa/Kinshasa | populated place | ||
| 204185 | Wundu | CD | Maniema | Kibombo | -3.53333 | 25.5 | 0 | Africa/Lubumbashi | populated place | ||
| 2315366 | Isenga | CD | Équateur | Bolomba | 0.16667 | 19.23333 | 0 | Africa/Kinshasa | populated place | ||
| 10048295 | Demesi | CD | Haut-Katanga | Pweto | -8.19791 | 28.47015 | 0 | Africa/Lubumbashi | populated place | ||
| 2316122 | Bwitshi | CD | Kwango | Kahemba | -7.9024 | 18.07698 | 0 | Africa/Kinshasa | populated place | ||
| 8284252 | Tshintu | CD | Kasai-Central | Kazumba | -6.39237 | 22.01591 | 0 | Africa/Lubumbashi | populated place | ||
| 8438813 | Mukini-Lwambi | CD | Kasai-Central | Luiza | -7.45442 | 22.5628 | 0 | Africa/Lubumbashi | populated place | ||
| 219974 | Bafwamasia | CD | Haut-Uele | Wamba | 2.18834 | 27.63676 | 0 | Africa/Lubumbashi | populated place | ||
| 213842 | Katanga | CD | Lomami | Lubao | -5.26667 | 26 | 0 | Africa/Lubumbashi | populated place | ||
| 219596 | Biango | Banga,Biango | CD | Kasai | Ilebo | -5.4494 | 20.52279 | 0 | Africa/Lubumbashi | populated place | |
| 206619 | Omedji | CD | Sankuru | Kole | -4.09653 | 22.98456 | 0 | Africa/Lubumbashi | populated place | ||
| 2311872 | Nta | CD | Kinshasa | Kinshasa | -4.15275 | 15.7675 | 0 | Africa/Kinshasa | populated place | ||
| 2314257 | Kinzashi-Kitambwe | CD | Kwilu | Gungu | -5.83832 | 19.78357 | 0 | Africa/Kinshasa | populated place | ||
| 210344 | Lushekere | CD | Nord Kivu | Rutshuru Territory | -1.03209 | 29.11559 | 0 | Africa/Lubumbashi | populated place | ||
| 8434649 | Yanga | CD | Kwango | Kasongo-Lunda | -6.42504 | 17.4199 | 0 | Africa/Kinshasa | populated place | ||
| 203599 | Yasala | CD | Tshuapa | Ikela | -0.66667 | 22.6 | 0 | Africa/Kinshasa | populated place | ||
| 1105471 | Kalasa | CD | Lualaba | Mutshatsha | -10.715 | 25.77111 | 0 | Africa/Lubumbashi | populated place | ||
| 209757 | Mambasa | CD | Nord Kivu | Walikale | -0.47542 | 28.52942 | 0 | Africa/Lubumbashi | populated place | ||
| 10054856 | Kambwo | CD | Haut-Lomami | Bukama | -9.37515 | 26.04461 | 0 | Africa/Lubumbashi | populated place | ||
| 8447868 | Muhango | CD | Kwango | Kahemba | -7.79385 | 18.99305 | 0 | Africa/Kinshasa | populated place | ||
| 8250007 | Otaka | CD | Sankuru | Lusambo | -4.72963 | 23.24921 | 0 | Africa/Lubumbashi | populated place | ||
| 8463714 | Satshilumbu | CD | Lualaba | Dilolo | -10.41999 | 22.42037 | 0 | Africa/Lubumbashi | populated place | ||
| 2317292 | Baringa Deuxième | Baringa Deuxieme,Baringa Deuxième,Baringa II | CD | Kwango | Kenge | -5.50294 | 16.92369 | 0 | Africa/Kinshasa | populated place | |
| 209849 | Malembe-Lungambo | Malemba Lungambo,Malembe,Malembe-Lunga,Malembe-Lungambo | CD | Kasai | Ilebo | -4.60453 | 20.81142 | 0 | Africa/Lubumbashi | populated place | |
| 220301 | Angako | CD | Ituri | Aru | 3.07542 | 30.55129 | 0 | Africa/Lubumbashi | populated place | ||
| 8462243 | Mufinda | CD | Lualaba | Sandoa | -9.42747 | 23.56449 | 0 | Africa/Lubumbashi | populated place | ||
| 9529066 | Tshindamba | CD | Kwango | Kahemba | -6.86468 | 19.73461 | 0 | Africa/Kinshasa | populated place |
Democratic Republic of the Congo: Mapping the Pulse of a Continental Giant
A Geographer’s Obsession with Scale and Detail
The Democratic Republic of the Congo is more than a country—it is a continent within a continent. Spanning the heart of Africa, it stretches across equatorial forests, volcanic mountain chains, sprawling savannahs, and one of the world’s largest river basins. For a geographer, it’s the ultimate canvas: complex, dynamic, and demanding. Yet what makes the DRC particularly captivating is not just its size, but the intricate mosaic of cities, provinces, and administrative departments that structure its vastness.
Capturing that complexity with precision isn’t a luxury—it’s a necessity. Whether studying migration patterns, urbanization, or public infrastructure, accurate city-level data is the compass that guides any serious inquiry into the Congolese landscape.
Understanding the National Tapestry Through Its Cities
In the DRC, cities are more than settlements—they are hubs of history, trade, resilience, and transformation. From the bustling sprawl of Kinshasa to the strategic positioning of Lubumbashi and Goma, each urban center is shaped by regional realities and administrative ties.
Our comprehensive city database organizes every urban point within its corresponding province and subdivision, offering a clear and hierarchical structure. This enables users to trace economic gradients, monitor development imbalances, and design policies rooted in the geography of governance.
Latitude, Longitude, and the Geometry of Insight
In a country where vast distances and rugged terrain often separate cities from one another, latitude and longitude are more than coordinates—they are the language of connectivity. Spatial analysis in the DRC is only as good as the precision of its geodata.
Every city in our dataset is geolocated with pinpoint accuracy. This allows planners, researchers, and developers to visualize relationships across space: where transportation networks should expand, where resource accessibility gaps remain, and where interventions are most urgent.
Excel: The Essential Tool for Accessible, Actionable Geography
One of the most exciting developments in our dataset is the addition of the Excel (.xlsx) format. While we still offer CSV, SQL, JSON, and XML formats for technical and programmatic integration, Excel stands out as the most accessible gateway for users across disciplines.
With Excel, anyone—from local administrators to academic researchers—can filter cities by province, analyze population density distributions, or export maps with integrated coordinates and administrative links. It bridges the gap between raw data and real-world decisions.
Moreover, Excel's tabular clarity allows for layered analysis: comparing city growth rates, regional disparities, and infrastructure coverage—all with just a few clicks. This is geography made tangible, intuitive, and powerful.
A Foundation for Research, Policy, and Development
In a country like the DRC, where data inconsistencies can derail entire projects, our clean, structured dataset offers an invaluable resource. Each entry is more than a name—it is a reference point for investment, humanitarian work, urban planning, and environmental modeling.
Governments need it. NGOs rely on it. Developers build on it. And now, with the flexibility to access it in Excel format, a wider audience than ever can tap into the geography of the Congo with unprecedented ease.
Conclusion: Charting the Living Geography of the Congo
The Democratic Republic of the Congo cannot be understood in generalities. It must be explored city by city, province by province, coordinate by coordinate. Its challenges are local, its potential regional, its future national—and all of it is spatial.
Our database provides that essential foundation: a way to map, model, and navigate the Congolese urban landscape with precision. And with Excel now leading the way in format accessibility, this isn’t just geography—it’s geography you can act on.
